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🏗️ Data Warehouse and Analytics Project

A comprehensive data warehousing and analytics solution, from building a data warehouse to generating actionable insights. This project demonstrates industry best practices in data engineering and analytics.

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Project Details

🚀 Project Overview

This project demonstrates a comprehensive data warehousing and analytics solution, from building a data warehouse to generating actionable insights. Designed as a portfolio project, it highlights industry best practices in data engineering and analytics.

The project involves building a modern data warehouse using SQL Server to consolidate sales data from multiple sources, enabling analytical reporting and informed decision-making.

🏗️ Data Architecture

The data architecture for this project follows Medallion Architecture Bronze, Silver, and Gold layers:

  • Bronze Layer: Stores raw data as-is from the source systems. Data is ingested from CSV Files into SQL Server Database.
  • Silver Layer: This layer includes data cleansing, standardization, and normalization processes to prepare data for analysis.
  • Gold Layer: Houses business-ready data modeled into a star schema required for reporting and analytics.

🔧 Tech Stack & Technologies

SQL Server Express SQL Server Management Studio (SSMS) SQL Development ETL Pipeline Development Data Modeling Data Architecture Data Engineering Data Analytics DrawIO Notion Git

📊 Project Components

Data Architecture

Designing a Modern Data Warehouse Using Medallion Architecture Bronze, Silver, and Gold layers.

ETL Pipelines

Extracting, transforming, and loading data from source systems into the warehouse.

Data Modeling

Developing fact and dimension tables optimized for analytical queries using star schema.

Analytics & Reporting

Creating SQL-based reports and dashboards for actionable insights into customer behavior, product performance, and sales trends.

📁 Repository Structure

📂 data-warehouse-project/
├── 📁 datasets/
# 📦 Raw datasets used for the project (ERP and CRM data)
├── 📁 docs/
├── 📄 etl.drawio
├── 📄 data_architecture.drawio
├── 📄 data_catalog.md
├── 📄 data_flow.drawio
├── 📄 data_models.drawio
└── 📄 naming-conventions.md
├── 📁 scripts/
├── 📁 bronze/
├── 📁 silver/
└── 📁 gold/
├── 📁 tests/
├── 📄 README.md
├── 📄 LICENSE
├── 📄 .gitignore
└── 📄 requirements.txt

🎯 Skills Demonstrated

SQL Development
Data Architecture
Data Engineering
ETL Pipeline Development
Data Modeling
Data Analytics

📌 Key Features

  • Import data from two source systems (ERP and CRM) provided as CSV files
  • Cleanse and resolve data quality issues prior to analysis
  • Combine both sources into a single, user-friendly data model designed for analytical queries
  • Focus on the latest dataset only; historization of data is not required
  • Provide clear documentation of the data model to support both business stakeholders and analytics teams
  • Develop SQL-based analytics to deliver detailed insights into customer behavior, product performance, and sales trends

👨‍💻 About the Author

Hi there! I'm Abdelrahman Haroun. Experienced Data Analyst with 2+ years at Samsung, specializing in transforming complex data into actionable insights. Passionate about leveraging analytics to drive business decisions and optimize performance across various domains.

LinkedIn GitHub Portfolio Notion Project